云-SVM模型及在数控机床刀具磨损状态预测中的应用

摘要

数控机床刀具磨损不仅直接影响加工质量,而且还会导致加工设备损坏和加工安全事故,因此正确对刀具状态进行识别和预测具有重要的现实意义.结合云模型和支持向量机的优点,提出了包含输入层、云化层、SVM层、逆云化层和输出层等五层结构的云-SVM模型,利用该模型对刀具磨损状态的识别和预测进行了仿真,结果表明该模型能够较真实的识别和预测磨损状态,具有较强实用性.%The NC machine tool wear could not only directly affect machining quality, but also lead to damage of machining equipment and processing accident. Therefore, it has important practical significance to identify and predict the tool status accurately. Combined with the advantages of cloud model and SVM, cloud-SVM model which includes five-layers (input layer, cloud layer, SVM layer, against cloud layer and output layer) has been presented. The identification and prediction of tool wear has been simulated by this model, and the results show that this model can identify and predict tool wear status accurately and therefore is with strong practicality.